Automatic Centreline Extraction Algorithm for Complex 3D Objects

Summary of the technology

University of Manitoba researchers have developed and validated a novel, fully automated, centerline extraction method that produces one-pixel thin, continuous, and spatially accurate skeletons from complex 3D shapes in a computationally efficient manner.

The method uses a ‘divide and conquer’ algorithm, in which any 3D object is first sliced into a series of 2D images in X, Y and Z directions. A geometric (Voronoi) algorithm is then applied to each planar image in order to extract the 2D centerlines before recombining the information using an intersection technique that is able to reconstruct the centerline of the original 3D object.

University of Manitoba


This approach has been validated using both standard 3D benchmark objects, as well as more complex anatomical structures segmented from medical images, demonstrating that the method is able to extract accurate centerlines.

Unlike other centerline extraction methods, our algorithm is computationally efficient, requiring relatively short processing times for both the 3D benchmark objects as well as complex medical images and can be run on standard desktop computers.


This method has wide-ranging utility in the field of 3D medical imaging, including data reduction for large microscopy datasets, automated quantification of MRI and other medical imaging techniques. It is currently being developed for automated quantification of anatomical features from medical imaging data (e.g., MRI values along brain axons, vessel diameters along coronary arteries, etc.), but could be broadly applied to other medical and non-medical applications.


The method has already been validated and benchmarked using various 3D objects (including anatomical structures segmented from medical imaging data), and is now being developed for quantifying MRI characteristics along-structures (e.g., axons, blood vessels, etc.). However, the University is interested in discussing licensing opportunities with respect to how our automated 3D centerline approach could be integrated into commercial products in these and other fields.

Intellectual property status

  • Granted Patent
  • Patent application number :US15845205

Attached documents

Related Keywords

  • Electronics, IT and Telecomms
  • Imaging, Image Processing, Pattern Recognition
  • Industrial Technologies
  • Physical Sciences and Exact Sciences
  • 3D
  • Medical Health related
  • Medical imaging
  • Medical equipment
  • Electromedical and medical equipment

About University of Manitoba

The Partnerships and Innovation office works toward increasing the number of partnerships between our researchers and groups outside the University of Manitoba and moving inventions from research labs into practical applications that can be used around the world.

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